Applied AI Engineer, Startups (Physical AI)

Anthropic•San Francisco, CA

4d•Hybrid

About The Position

As an Applied AI Engineer on Anthropic’s Startups team, you will serve as a trusted technical advisor to AI-native startups building in physical-world fields such as robotics, semiconductors, aerospace, manufacturing, and civil infrastructure. You will work with companies that incorporate Claude into products and with those using Claude to design, test, and operate hardware and engineering systems. You will lead technical engagements with startup software and hardware teams, advising on implementation and agent design and helping them apply AI across real engineering workflows. Working with Applied AI Architects, Account Executives, and Anthropic’s Product, Engineering, and Research teams, you will help startups build with Claude at the edge of what is possible. You will draw on AI engineering expertise and physical engineering domain knowledge to create evaluation frameworks, scalable architectures, technical resources, prototypes, and reusable implementations. The role also involves identifying common challenges in applying AI to physical systems and sharing insights across Anthropic, developing technical content and community programming, and traveling to customer sites for workshops and implementation guidance. Anthropic’s mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The company is a public benefit corporation headquartered in San Francisco. The role follows a location-based hybrid policy: staff are currently expected to be in an office at least 25% of the time, though some roles may require more. Visa sponsorship may be available, subject to role and candidate circumstances.

Requirements

Deep engineering experience in a physical discipline such as mechanical, electrical, aerospace, robotics, semiconductor, manufacturing, or civil engineering, gained by designing, building, or operating real hardware.
At least 4 years of technical experience as a software engineer, ML or research engineer, robotics or controls engineer, hardware or systems engineer, or technical founder.
Either production experience building LLM-powered applications—including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale—or a track record of applying AI to engineering work in design, simulation, testing, or production.
Experience with startups or high-growth companies and interest in working with founders and small teams that move quickly.
Strong technical communication skills, including the ability to translate complex AI concepts into architectural decisions and actionable implementation plans for software and hardware audiences.
Ability to run technical workshops, hackathons, or developer-focused events.
Collaborative approach to cross-team work and ability to quickly get up to speed in new domains.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.
Required field of study: a field relevant to the role, demonstrated through coursework, training, or professional experience.

Responsibilities

Advise high-potential startups building in the physical world on applying Claude to their products and to their hardware design, testing, and operations.
Work directly with startup software and hardware teams through pair programming and architecture reviews, and understand their engineering workflows from design and simulation through testing, production, and operations.
Develop prototypes and technical documentation, including evaluation suites, benchmarks based on real engineering tasks, AI engineering techniques, and architecture diagrams.
Create reference implementations and sample code, including integrations between Claude and CAD, simulation, design tools, or industrial automation.
Collaborate with Applied AI Architects to maintain context and continuity across customer engagements.
Identify recurring challenges in applying AI to physical systems, develop repeatable evaluations and solutions, and contribute insights to Product, Engineering, Research, and the broader Applied AI team.
Create technical content for startup audiences, including documentation, tutorials, and sample code.
Support community engagement through hackathons, webinars, technical office hours, and startup-focused events.
Travel to customer sites for workshops, implementation guidance, and relationship building.